Understanding Lodging in Oat (Avena sativa L.) through Root, Stem, and Leaf Characteristics
Notice bibliographique
Résumé
Lodging is the permanent displacement of stems from their upright positions and is a critical issue for oat (Avena sativa L.) producers as it reduces harvestability, yield, and quality, while increasing disease load. To help prevent lodging, producers can utilize management strategies that include: (i) agronomic practices, such as using plant growth regulators or altering seeding, nitrogen or irrigation rates, and (ii) the choice of cultivar. Typically, the development of lodging-resistant cultivars entails the visual assessment of lodging when suitable environmental conditions or management techniques promote lodging. However, in the absence of such conditions it becomes challenging to develop lodging resistant cultivars. It is therefore important to develop methods that will allow plant breeders to continue selecting for lodging resistant breeding lines, even in the absence of visual lodging, by understanding and assessing the underlying traits relevant to lodging. Given the equally important genetic and agronomic influences on lodging, this thesis had three main objectives: 1) to evaluate stem biomechanical, root crown architecture, and whole plant traits to determine those which are correlated to lodging resistance, 2) to understand the impact of seeding rate on traits important to lodging resistance, and 3) to assess the potential of indoor root imaging to identify root system traits which are important for lodging resistance. To address the first objective, 14 spring oat genotypes adapted to western Canada and representing a diverse range of height and lodging resistance were grown over six site-years and assessed for whole plant, stem, and root crown traits. A correlation analysis showed that plant height, internode length, flag leaf angle, whole plant bending resistance, root plate angle, and stem inner and outer diameters were significantly associated to lodging resistance. Imaging of root crowns revealed that root volume and root length were significantly correlated to lodging. A decision tree created using inner diameter, internode length, and force per panicle was able to predict lodging resistance with an accuracy of 79%. Finally, a structural equation model showed that plant height, internode length, flag leaf angle, bending resistance, root plate angle, and inner diameter all directly influenced lodging. To address the second objective, four genotypes were grown at three seeding rates: 200 (low recommended rate), 300 (high recommended rate), and 400 (very high rate) plants/m2. Analysis of variance and post-hoc testing revealed that whole plant bending resistance, stem outer and inner diameters, solidity, and root plate spread were significantly impacted by seeding rate and displayed no cultivar or site-year interactions. Plant height displayed a seeding rate by genotype interaction, while both root volume and root length displayed three-way interactions between seeding rate, genotype and site year. Overall, the lowest seeding rate provided the greatest benefit towards reducing lodging without negatively impacting yield. For the third objective, seedlings of 22 oat genotypes, including the 14 field-grown genotypes from objective 1, were assessed using 2-dimensional hydroponic pouch imaging from early germination to the 4 leaf-emergence stage. Image analysis of 23 root system traits revealed that the number of holes in the root system and median number of roots were significantly correlated to lodging rating. When assessed visually, it was observed that genotypes with higher lodging resistance had a larger number of lateral roots that were also longer, which suggested root systems with potentially greater soil gripping capacities. Growth of the 14 field-grown genotypes in rhizoboxes did not reveal any traits significantly correlated to lodging, however, tiller number was correlated to tiller angle and height. Overall, this thesis demonstrated that oat lodging resistance is complex, being influenced by several above-ground architectural traits, mechanical traits, and root architecture traits, with resistance being attainable via different combinations of these traits. Some traits, such as plant height, whole plant bending resistance and flag leaf angle, are suitable for early-generational screening in breeding programs with inexpensive and high-throughput measurement. Other traits such as internode length, stem diameters and field root architecture traits may need to be reserved until the final stages of breeding due to their low throughput and more technical nature to measure. Finally, this thesis indicated that a lower seeding rate (200 plants/m2) would be most beneficial to reduce lodging. This rate altered values of five lodging-related traits to improve lodging resistance, with four target traits showing no cultivar or site-year interactions, thus indicating the universal benefit to oat producers of using a lower seeding rate to decrease lodging risk.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».