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Enregistrement W2145460047 · doi:10.1111/j.1439-0523.2011.01936.x

Breeding for resistance to ear rots caused by <i>Fusarium</i> spp. in maize – a review

2011· review· en· W2145460047 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevuePlant Breeding · 2011
Typereview
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueMycotoxins in Agriculture and Food
Établissements canadiensAgriculture and Agri-Food Canada
Organismes subventionnairesnon disponible
Mots-clésFusariumBiologyInoculationGibberellaResistance (ecology)Fusarium culmorumHybridGenotypeMycotoxinFungi imperfectiAgronomyHorticultureVeterinary medicineBotanyGeneticsGene

Résumé

récupéré en direct d'OpenAlex

With 2 tables Abstract Ear rots caused by different Fusarium spp. are one of the most dangerous food and feed safety challenges in maize production. At present, the majority of the inbreds and hybrids are susceptible. Gibberella and Fusarium ear rots (caused by Fusarium graminearum and Fusarium verticillioides , respectively) are the two main diseases, but more than 10 further Fusarium spp. cause ear rots. Natural infection is initiated by a mixture of the local Fusarium spp., but usually one species predominates. Many maize breeders rely on natural infection to create sufficient levels of disease severity for selection‐resistant genotypes; however, there are few locations where the natural infection is sufficiently uniform to make this selection efficient and successful. Thus, an artificial inoculation method normally performed with one fungal species is now used by more breeders. Most published papers on breeding for ear rot resistance are focused on either F. graminearum or F. verticillioides , and reports involving both or more Fusarium spp. are rare. Several reports support the hypothesis that resistance to multiple species especially F. graminearum, F. culmorum and F. verticillioides may be common. Significant differences in genotypic resistance after inoculation exist. Resistance to the two major modes of fungal entry into the ear, via the silk or through kernel wounds, is not correlated in all genotypes. The reason is not clear. When silk channel resistance was assessed, the data from natural and artificial inoculation trials correlated well. Analogous data relating to kernel resistance have not been published. Both native and exotic sources of resistance are important, but surprisingly little information is available. Few papers report on the use of artificial inoculation during inbred development. Most of the publications on inoculation are concerned with testing at later stages when combining ability is tested. Inbreds differ in general and specific combining ability for ear rot resistance. The expression of resistance to disease severity and resistance to toxins is often used as synonyms, but in fact they are not. Higher resistance to visual disease severities mostly results in lower toxin contamination, and the resistance level seems to be the most important factor regulating the toxin content. The mode of inheritance of resistance appears to differ: additive, possibly non‐additive effects, digenic (dominant) and polygenic patterns have been identified. Improved phenotyping methods that take into account the influence of stalk rot and the use of several independent isolates are available. The QTLs mostly exhibit small effects and some are validated; however, marker‐assisted selection in breeding cannot yet be foreseen. As the severity of natural infections tends to correlate with the artificial inoculation results, the incorporation of artificial inoculation methods in breeding programmes is now the most important task. As genotypic resistance differences between hybrids are high, the registration of hybrids should consider the use of the inoculation tests to choose most resistant hybrids for commercial production. This is the most rapid way to increase feed safety.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,636
Score d'incertitude au seuil0,975

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,085
Tête enseignante GPT0,271
Écart entre enseignants0,185 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle